Companies hire people because they believe the organization will be better off with them than they would be without them. Said differently, the decision to hire someone will ideally result in higher organizational productivity and performance. The hope is that a newly hired employee will produce more than they cost, otherwise they wouldn’t have hired them. The pain comes when some newly hired employees end up costing more than they produce, or they don’t produce nearly enough as compared to what they could, representing an opportunity cost.
Thus, the ability to identify people who have the capability to be more productive for the organization is a central priority for most companies. Conversely, the ability to screen out candidates who would be a poor hire is of equal importance. Bad hires cost you in time, energy and money, stemming from activities related to recruiting, onboarding, training, severance and more. So how do organizations separate the candidates who will produce higher organizational productivity from those who won’t?
The labor market is the “place” where people look for these jobs and organizations look for people to do these jobs. This is generally described, among other things, as a “matching” problem between these organizations and job searchers. There are qualified people that want jobs, but are having difficulty pairing up with organizations who are looking for qualified people. Among other things, there are informational gaps regarding a job searcher's abilities that an organization needs to resolve before a “match” is successfully facilitated.
There are generally two key ways in which these information asymmetries are resolved: signalling and screening. Signalling relies on candidates doing something to differentiate themselves, such as obtaining a college degree. Screening involves the organization finding ways to obtain job relevant information from candidates in real time. The information exchanged through both of these mechanisms plays a vital role in certifying the quality of talent, where employers can make an inferential leap about a candidate's skills and ability to do a job.
This crucial exchange of information between job market actors (applicants and organizations) is essentially the process of personnel selection. The hiring process is fundamentally about gathering data points and reducing uncertainty about a candidate’s skills & capabilities. Hiring is fundamentally about capital allocation: How can you as the person making a hiring decision most productively deploy the capital that has been allocated to you and bring the largest return on investment to your team and your company?
In a world of perfect information, this decision of who to hire (and whom not to hire) would be obvious, because you’d truly know a candidate's capabilities and how they would turn out in your organization. However, informationally and otherwise, the world is far from perfect. As the person making a hiring decision, you’re always making the best decisions you can with the information you have on hand, which we know to be imperfect and incomplete. The job of the person making that decision then is to be an effective calibrator of talent: to get as close to truth as possible in regards to that candidate's knowledge, skills, and abilities that will likely help them perform well on the job. Here, you’re aiming for a minimum threshold of certainty before making a decision, and then ultimately, have to make a prediction based on the limited information they’ve obtained in the hiring process. Effective calibration of talent then requires employers to rely on a variety of screening and signaling mechanisms to help them spot talent a priori.
Companies traditionally rely on age-old methods for assessing and evaluating talent to obtain these “signals” for their organizations: Interviews, resume screens, reference checking and more. These methods can be incredibly valuable in their own regard (when done right). And while these are certainly important components of most hiring processes, it’s also widely recognized that these methods for assessing talent are laden with imperfection. These methods can be incredibly subjective, data absent and unreliable. They tend to 1) be inconsistent across multiple candidates, 2) attribute value to job irrelevant factors in a potential candidate, 3) demonstrate an incredible amount of unfairness (mostly unintended) towards certain groups of people, and lastly 4) do a fairly poor job at predicting who is going to be a good employee. Relying solely on these lagging indicators of talent is a bit like a soccer coach deciding who should be on their soccer team without actually seeing anybody play soccer. Intuitively, that doesn’t make sense to most of us, yet it’s what most professional organizations do today.
The use of valid and reliable assessments is a proven medium for reducing the informational uncertainties in the hiring process. They enable hiring managers to get access to real time performance data via candidate completion of the assessment, while simultaneously mitigating unfairness and increasing access to opportunity for certain groups of candidates. The purpose of deploying assessments to screen talent is to ultimately obtain more objective, useful and data driven information that can help recruiters and managers make higher quality and more informed selection decisions. With simulation based assessments in particular (the primary method by which Hexient assessments are designed), candidates are presented with real world situations that they will encounter on the job they’re applying for. These assessments offer organizations the opportunity to obtain high impact candidate information they might not have gotten otherwise by relying on those traditional evaluation methods alone. Although imperfect in their own right, assessments offer an incredibly viable option to gather accurate information about an individual's job relevant characteristics.
So now, armed with this information, should organizations stop interviewing and reviewing resumes altogether and adopt assessments as their only method of candidate evaluation? Not exactly. Selection decisions should never be made on the basis of one point of evaluation. Rather, most organizations can construct hiring processes that consist of multiple points of evaluation, with the reasoning being that each selection procedure used in the process will provide incremental value and information to help make better decisions, assuming they are job related.
We use multiple methods of evaluation because there is no such thing as a silver bullet for hiring. The honest answer to who is going to be the best worker for the job is always “I don’t know”, as you’re being asked to predict the future of another person. As we’ve seen, the question is unanswerable with available information and limited human judgement. Employers, however, don’t have the luxury of throwing their hands in the air and saying “I don’t know so let’s not hire anyone”. In fact, the compressed timelines associated with making hiring decisions necessitates employers to rely on more easily accessible proxy metrics for talent and making the best decision you can with available information and judgement. The goal is not complete certainty, because that is unattainable, but enough of a reduction of uncertainty can help us make better decisions.
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